A new simulation-based metaheuristic approach in optimization of bilayer composite sheet hydroforming
Simulated annealing which has been recently used in engineering applications is one of the most popular metaheuristic algorithms to solve optimization problems. In this work, an adaptive simulated annealing (SA) technique coupled with an adaptive finite element method is proposed and developed to op...
Saved in:
Published in: | Journal of the Brazilian Society of Mechanical Sciences and Engineering Vol. 39; no. 10; pp. 4011 - 4020 |
---|---|
Main Authors: | , , , |
Format: | Journal Article |
Language: | English |
Published: |
Berlin/Heidelberg
Springer Berlin Heidelberg
01-10-2017
Springer Nature B.V |
Subjects: | |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Summary: | Simulated annealing which has been recently used in engineering applications is one of the most popular metaheuristic algorithms to solve optimization problems. In this work, an adaptive simulated annealing (SA) technique coupled with an adaptive finite element method is proposed and developed to optimize bilayer composite sheet hydroforming process. The aim of this combinatorial procedure is to obtain optimal forming pressure loading path to develop a new definition of SA algorithm parameters, to create an adaptive finite element (FE) code, to produce desired products with minimum thinning, and to avoid wrinkling and bursting failures. All of the effective SA parameters including Markov chain number, cooling function, initial temperature, and final temperature are redefined and developed to reduce excess iterations in FE simulations, hence saving the time and energy during the optimization process. The proposed optimization technique is employed to investigate the effect of layers sequence and thickness ratio on minimum cup thinning and optimal pressure load in hydroforming of aluminum/steel composite sheet. The experimental results demonstrated that the proposed adaptive method could be a reliable technique for optimization of processes with a large search space. It is also shown that it provides precise results in a shorter time by redefining the algorithm parameters. |
---|---|
ISSN: | 1678-5878 1806-3691 |
DOI: | 10.1007/s40430-017-0720-1 |